alt Hacker NewsI think the point is that there are better engineering artifacts to review instead of lines of code. Encoding the decisions, structure, requirements, testing, monitoring, then reviewing those and having AI generate and regenerate code based on them. The code itself doesn't matter if enough thought and rigor has gone into the structure that produces the code.
> What does "ideal" mean here? When I was growing up "show your work" was the rule for all examinations. Why? Because we're working to improve mental models and thought processes for the next generation, not just products we will release tomorrow.
They're saying that the mental models and thought processes are incredibly important but that code is not the place for that work to live.
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> They're saying that the mental models and thought processes are incredibly important but that code is not the place for that work to live.
They’re important for discussion and brainstorming. They’re also important for sharing context before reviewing. But code is the only perfect representation in terms of semantics of what the computer will do.
You can have all the diagram and all the proses you want, but they’re still ambiguous.
> They're saying that the mental models and thought processes are incredibly important but that code is not the place for that work to live.
What I meant is that, insofar as some work has been produced with a human mind involved and where imperfect abstractions are used, one should not for whatever idealistic reasons push for reviewing the work at some coarser granularity than the details which are readily available. That's a way to foster and encourage mistakes, in both the work and in the mental model.
So when you say that code is not the place for that work to live (or more closely to the line I disagree with, that code is not an 'ideal' artifact to review), you are essentially purporting that there is a perfect abstraction that can generally be trusted, which I disagree is currently the case for an LLM spec versus produced code.